Abstract Introduction The definition of human sexual response and sexual dysfunctions are largely based on Masters 1985) used a direct measure of neural activity, namely EEG. However, these past EEG studies were conducted on small samples and without performing any statistical analysis. Objective The current study was conducted to identify the electrophysiological correlates of female sexual response phases (excitement, plateau, orgasm, resolution) using a 64-active-electrodes EEG during automated masturbation. Methods To this end, we developed a new experimental protocol allowing data collection to be conducted at the participant’s house, to maximize privacy and ecological validity. In order to reduce the EEG signal associated with hand-movement during masturbation, an external vibrator was fixed on a microphone stand, and participants were asked to modulate stimulation by moving their hips. Duration of each sexual response phase was determined subjectively, using a button press. After preprocessing, data from 22 participants were retained in the final sample (of an original sample of n=27). Analyses were conducted in two steps. First, power spectral density was calculated using a Discrete Prolate Spheroidal Sequences-based multitaper Fourier transform in the frequency range 1–45Hz. One-way repeated measures ANOVA revealed significant differences in power across conditions. Second, five frequency bands were defined for subsequent analyses: Delta (2–4 Hz), Theta (4–7 Hz), Alpha (8–12 Hz), Beta (13–30 Hz), and Gamma (31–45 Hz). Statistical comparisons across sexual phases and rest conditions were assessed with non-parametric cluster-based permutation tests, to control for multiple comparisons Results Two significant clusters were identified (Figure 1). Cluster 1 showed a decrease in power in low frequencies (6–12 Hz, p = 0.0058) in parietal sites during masturbation as compared to rest. Cluster 2 (17–41 Hz, p = 1e−05) instead showed an increase in high frequencies in middle-frontal sites during masturbation as compared to rest. Post-hoc analyses showed that low-gamma power (31-45 Hz) discriminates across sexual response phases, as it gradually increases going from excitement to plateau to orgasm (Figure 2). Conclusions This is the first study to use a direct measure of neural activity across the full sexual response cycle, allowing comparisons across phases of sexual response. Findings showed that changes in EEG low-gamma power discriminate between sexual response phases. Previous studies indicate that gamma power increases with tactile stimulus intensity (Rossiter et al., 2013) but even more with nociceptive (vs vibrotactile, auditory, visual) stimuli (Liberati et al., 2018). Our results expand these previous findings, suggesting that gamma power may also index pleasure intensity. Moreover, this finding both reinforces and complements Masters and Johnson (1966)’s findings, since our brain results on gamma power parallel the body physiological changes they identified. These results open a promising new avenue by providing a reference for empirically testing centrally acting neuropharmacological agents (such as Flibanserin) used to enhance female sexual response and for exploring novel treatments for orgasm-related difficulties. Disclosure No
Bittoni et al. (Mon,) studied this question.